Abstract

Background

As microbial ecologists take advantage of high-throughput sequencing technologies
to describe microbial communities across ever-increasing numbers of samples, new analysis
tools are required to relate the distribution of microbes among larger numbers of
communities, and to use increasingly rich and standards-compliant metadata to understand
the biological factors driving these relationships. In particular, the Earth Microbiome
Project drives these needs by profiling the genomic content of tens of thousands of
samples across multiple environment types.

Findings

Features of EMPeror include: ability to visualize gradients and categorical data,
visualize different principal coordinates axes, present the data in the form of parallel
coordinates, show taxa as well as environmental samples, dynamically adjust the size
and transparency of the spheres representing the communities on a per-category basis,
dynamically scale the axes according to the fraction of variance each explains, show,
hide or recolor points according to arbitrary metadata including that compliant with
the MIxS family of standards developed by the Genomic Standards Consortium, display
jackknifed-resampled data to assess statistical confidence in clustering, perform
coordinate comparisons (useful for procrustes analysis plots), and greatly reduce
loading times and overall memory footprint compared with existing approaches. Additionally,
ease of sharing, given EMPeror’s small output file size, enables agile collaboration
by allowing users to embed these visualizations via emails or web pages without the
need for extra plugins.

Conclusions

Here we present EMPeror, an open source and web browser enabled tool with a versatile
command line interface that allows researchers to perform rapid exploratory investigations
of 3D visualizations of microbial community data, such as the widely used principal
coordinates plots. EMPeror includes a rich set of controllers to modify features as
a function of the metadata. By being specifically tailored to the requirements of
microbial ecologists, EMPeror thus increases the speed with which insight can be gained
from large microbiome datasets.